63 lines
1.6 KiB
Markdown
63 lines
1.6 KiB
Markdown
<!-- Note: This file is automatically generated from source code comments. Changes made in this file will be overridden. -->
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# Function quantileSeq
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Compute the prob order quantile of a matrix or a list with values.
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The sequence is sorted and the middle value is returned.
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Supported types of sequence values are: Number, BigNumber, Unit
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Supported types of probability are: Number, BigNumber
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In case of a (multi dimensional) array or matrix, the prob order quantile
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of all elements will be calculated.
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## Syntax
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```js
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math.quantileSeq(A, prob[, sorted])
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math.quantileSeq(A, [prob1, prob2, ...][, sorted])
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math.quantileSeq(A, N[, sorted])
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```
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### Parameters
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Parameter | Type | Description
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--------- | ---- | -----------
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`data` | Array, Matrix | A single matrix or Array
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`probOrN` | Number, BigNumber, Array | prob is the order of the quantile, while N is the amount of evenly distributed steps of probabilities; only one of these options can be provided
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`sorted` | Boolean | =false is data sorted in ascending order
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### Returns
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Type | Description
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---- | -----------
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Number, BigNumber, Unit, Array | Quantile(s)
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### Throws
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Type | Description
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---- | -----------
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## Examples
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```js
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math.quantileSeq([3, -1, 5, 7], 0.5) // returns 4
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math.quantileSeq([3, -1, 5, 7], [1/3, 2/3]) // returns [3, 5]
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math.quantileSeq([3, -1, 5, 7], 2) // returns [3, 5]
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math.quantileSeq([-1, 3, 5, 7], 0.5, true) // returns 4
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```
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## See also
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[median](median.md),
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[mean](mean.md),
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[min](min.md),
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[max](max.md),
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[sum](sum.md),
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[prod](prod.md),
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[std](std.md),
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[variance](variance.md)
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